Massive advancements have been noticed on the Internet of Things (IoT) integrating smart
Homes Energy Management Systems (HEMSs). In the literature, many reviews have been …

Biomedical scientific literature is growing at a very rapid pace, which makes increasingly
difficult for human experts to spot the most relevant results hidden in the papers …

Most sequencing data analyses start by aligning sequencing reads to a linear reference
genome, but failure to account for genetic variation leads to reference bias and confounding …

Attributed graphs are used to model a wide variety of real-world networks. Recent graph
convolutional network-based representation learning methods have set state-of-the-art …

Background Genetic ancestry, inferred from genomic data, is a quantifiable biological
parameter. While much of the human genome is identical across populations, it is estimated …

Human gene sequences are considered a primary source of comprehensive information
about different body conditions. A wide variety of diseases including cancer, heart issues …

Graph clustering is one of the popular techniques in data mining, which is widely used in
social network analysis, recommendation system and anomaly detection. The existing …

Motivation We present dnadna, a flexible python-based software for deep learning inference
in population genetics. It is task-agnostic and aims at facilitating the development …

Most sequencing data analyses start by aligning sequencing reads to a linear reference
genome. But failure to account for genetic variation causes reference bias and confounding …

Smart cities aim to efficiently address the challenges posed by urbanization, energy
consumption, environmental sustainability, and improvement of living standards. The …